
import pandas as pd #libreria de visualizacion de texto
import numpy as np #libreria de operaciones matematicas
import string #analisis de texto
import re #operaciones de texto
import zipfile #unzip files
import nltk #libreria para analisis
from nltk.corpus import stopwords #eliminacion de stopwrod
from wordcloud import WordCloud #graficas
import matplotlib.pyplot as plt #graficas
from nltk.sentiment.vader import SentimentIntensityAnalyzer #polaridad del texto


file_name = 'GrammarandProductReviews.csv.zip'
with zipfile.ZipFile(file_name, 'r') as file:
    file.extractall()
datos=pd.read_csv('GrammarandProductReviews.csv')
datos.head()


datos = datos.dropna(subset=['reviews.text'])


datos['reviews.text'] = datos['reviews.text'].apply(lambda line: line.lower())
datos.head()


def remove_punctuations(text):
    for punctuation in string.punctuation:
        text = text.replace(punctuation, '')
    return text
datos['reviews.text'] = datos['reviews.text'].apply(remove_punctuations)
datos.head()


datos['reviews.text'] = datos['reviews.text'].apply(lambda x: re.split('https:\/\/.*', str(x))[0])
datos.head()


datos.astype(str).apply(lambda x: x.str.encode('ascii', 'ignore').str.decode('ascii'))
datos.head()


stop = stopwords.words('english')

datos['reviewsnostop.text'] = datos['reviews.text'].str.lower().str.split() 

datos['reviewsnostop.text'] = datos['reviewsnostop.text'].apply(lambda x: [item for item in x if item not in stop])
datos.head()


datos['reviews.text'] = [' '.join(map(str, l)) for l in datos['reviewsnostop.text']]

datos.head()


def most_used_words(data):
    wordcloud = WordCloud(
        background_color='white',
        stopwords=stop,
        max_words=20,
        max_font_size=40, 
        scale=3,
        random_state=1).generate(str(data))

    fig = plt.figure(1, figsize=(15, 15))
    plt.axis('off')
    plt.imshow(wordcloud)
    plt.show()
    
#r1 = datos.loc[datos['reviews.rating']==1, ['reviews.text']]
#most_used_words(r1)


import seaborn as sns

sns.countplot(datos['reviews.rating'])

/home/marisamv/.local/lib/python3.6/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning

<AxesSubplot:xlabel='reviews.rating', ylabel='count'>


def classi(rating):
    if rating < 3:
        return 'Neg'
    elif rating == 3:
        return 'Neutral'
    else:
        return 'Pos'
datos['review.class'] = datos['reviews.rating'].apply(lambda rate: classi(rate))
pos = {} #dic con counters
neg = {}
    
for review, classif in zip(datos['reviews.text'], datos['review.class']):
    text = review.split(' ')
    for word in text:
        if word not in stop and word != '':
            if classif == 'Pos':
                counter = pos.get(word)
                if counter:
                    pos[word] = counter + 1
                else:
                    pos[word] = 1
            elif classif == 'Neg':
                counter = neg.get(word)
                if counter:
                    neg[word] = counter + 1
                else:
                    neg[word] = 1


#pos


#neg


# add sentiment anaylsis columns
sid = SentimentIntensityAnalyzer()
datos['reviewsPol.text'] = datos['reviews.text'].apply(lambda x: sid.polarity_scores(x))
datos = pd.concat([datos.drop(['reviewsPol.text'], axis=1), datos['reviewsPol.text'].apply(pd.Series)], axis=1)
datos.head()


def classification(rating):
    if rating < 0:
        return 'Neg'
    elif rating == 0:
        return 'Neutral'
    else:
        return 'Pos'
datos['review.classification'] = datos['compound'].apply(lambda rate: classification(rate))
datos.head()


# from geopy.geocoders import Nominatim
# geolocator = Nominatim(user_agent='myapplication')

# ciudades = pd.DataFrame(datos['reviews.userCity'].value_counts().sort_values(ascending=False))
# ciudades.reset_index(level=0, inplace=True)

# ciudades.columns = ['Ciudades','Freq']
# print(ciudades)
# lats=[]
# lons=[]
# for i in range(len(ciudades)):        
#     location = geolocator.geocode(ciudades['Ciudades'][i])
#     try:
#         hola = location.raw
#         lons.append(hola.get('lon'))
#         lats.append(hola.get('lat'))
#     except:
#         lons.append(0)
#         lats.append(0)'''


# '''ciudades = ciudades[:len(lats)]
# ciudades['lat'] = lats
# ciudades['lot'] = lons

# ciudades.to_csv('ciudades_freq.csv', index = False)'''


import plotly.graph_objects as go

import pandas as pd

df = pd.read_csv('ciudades_freq.csv')
df['text'] = df['Ciudades'] + '<br>Frecuencia ' + (df['Freq']).astype(str)
limits = [(0,2),(3,10),(11,20),(21,50),(50,70)]
colors = ["royalblue","crimson","lightseagreen","orange","lightgrey"]
cities = []
scale = 5000

fig = go.Figure()

for i in range(len(limits)):
    lim = limits[i]
    df_sub = df[lim[0]:lim[1]]
    fig.add_trace(go.Scattergeo(
        locationmode = 'USA-states',
        lon = df_sub['lot'],
        lat = df_sub['lat'],
        text = df_sub['text'],
        marker = dict(
            size = df_sub['Freq'],
            color = colors[i],
            line_color='rgb(40,40,40)',
            line_width=0.5
        ),
            name = '{0} - {1}'.format(lim[0],lim[1])))

fig.update_layout(
        title_text = 'Reviews realizadas por usuarios ordenados por Ciudad<br>',
        showlegend = True,
        geo = dict(
            scope = 'usa',
            landcolor = 'rgb(217, 217, 217)',
        )
    )

fig.show()


# Creating trace1
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
df = datos[:2500]
df['text'] = df['manufacturer'] + '<br> Product <br>' + df['name'] + '<br> Clasificacion<br>' + df['review.class']

# Creating trace2
trace2 = go.Scatter(
                    x = df.neg,
                    y = df.pos,
                    mode = "markers",
                    marker = dict(color = 'rgba(80, 26, 80, 0.8)'),
                    text= df.text)
data = [trace2]
layout = dict(title = 'Diagrama de Puntos en el cual se puede ver el coficiente positvio y negativo de 2500 reviews<br>En el texto podemos observar el productor y el nombre del producto',
              xaxis= dict(title= 'Coeficiente negativo',ticklen= 5,zeroline= False),
              yaxis= dict(title= 'Coeficiente positivo',ticklen= 5,zeroline= False)
             )
fig = dict(data = data, layout = layout)
iplot(fig)

/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy


# pos = datos.loc[datos['review.classification'] == 'Pos']
# neg = datos.loc[datos['review.classification'] == 'Neg']

# feq_pos = pd.DataFrame(pos.groupby(["reviews.userCity", "brand"]).size().sort_values(ascending=False))
# from geopy.geocoders import Nominatim
# geolocator = Nominatim(user_agent='myapplication')
# feq_pos.reset_index(level=0, inplace=True)
# feq_pos.reset_index(level=0, inplace=True)


# feq_pos.columns = ['Ciudades','Brand', 'Freq']
# print(feq_pos)
# lats=[]
# lons=[]
# for i in range(len(feq_pos)):        
#     location = geolocator.geocode(feq_pos['Ciudades'][i])
#     try:
#         hola = location.raw
#         lons.append(hola.get('lon'))
#         lats.append(hola.get('lat'))
#     except:
#         lons.append(0)
#         lats.append(0)
    

#pd.DataFrame(datos['reviews.userCity'].value_counts().sort_values(ascending=False))


# feq_pos = feq_pos[:len(lats)]
# feq_pos['lat'] = lats
# feq_pos['lot'] = lons
# feq_pos.columns = ['Brand','Ciudades', 'Freq','lat','lot']

# feq_pos.to_csv('feq_pos.csv', index = False)


# feq_neg = pd.DataFrame(neg.groupby(["reviews.userCity", "brand"]).size().sort_values(ascending=False))
# from geopy.geocoders import Nominatim
# geolocator = Nominatim(user_agent='myapplication')
# feq_neg.reset_index(level=0, inplace=True)
# feq_neg.reset_index(level=0, inplace=True)


# feq_neg.columns = ['Ciudades','Brand', 'Freq']
# print(feq_neg)
# lats=[]
# lons=[]
# for i in range(len(feq_neg)):        
#     location = geolocator.geocode(feq_neg['Ciudades'][i])
#     try:
#         hola = location.raw
#         lons.append(hola.get('lon'))
#         lats.append(hola.get('lat'))
#     except:
#         lons.append(0)
#         lats.append(0)


# feq_neg = feq_neg[:len(lats)]
# feq_neg['lat'] = lats
# feq_neg['lot'] = lons
# feq_neg.columns = ['Brand','Ciudades', 'Freq','lat','lot']


# feq_neg.to_csv('feq_neg.csv', index = False)


import plotly.graph_objects as go

import pandas as pd

df = pd.read_csv('feq_pos.csv')
df['text'] = df['Ciudades'] + '<br>Frecuencia ' + (df['Freq']).astype(str) + '<br>Brand ' + (df['Brand']).astype(str)
limits = [(0,2),(3,10),(11,20),(21,50),(50,70)]
colors = ["royalblue","crimson","lightseagreen","orange","lightgrey"]
cities = []
scale = 5000

fig = go.Figure()

for i in range(len(limits)):
    lim = limits[i]
    df_sub = df[lim[0]:lim[1]]
    fig.add_trace(go.Scattergeo(
        locationmode = 'USA-states',
        lon = df_sub['lot'],
        lat = df_sub['lat'],
        text = df_sub['text'],
        marker = dict(
            size = df_sub['Freq'],
            color = colors[i],
            line_color='rgb(40,40,40)',
            line_width=0.5
        ),
            name = '{0} - {1}'.format(lim[0],lim[1])))

fig.update_layout(
        title_text = 'Reviews positivas realizadas por usuarios ordenados por Ciudad y marcas<br>',
        showlegend = True,
        geo = dict(
            scope = 'usa',
            landcolor = 'rgb(217, 217, 217)',
        )
    )

fig.show()


import plotly.graph_objects as go

import pandas as pd

df = pd.read_csv('feq_neg.csv')
df['text'] = df['Ciudades'] + '<br>Frecuencia ' + (df['Freq']).astype(str) + '<br>Brand ' + (df['Brand']).astype(str)
limits = [(0,2),(3,10),(11,20),(21,50),(50,70)]
colors = ["royalblue","crimson","lightseagreen","orange","lightgrey"]
cities = []
scale = 5000

fig = go.Figure()

for i in range(len(limits)):
    lim = limits[i]
    df_sub = df[lim[0]:lim[1]]
    fig.add_trace(go.Scattergeo(
        locationmode = 'USA-states',
        lon = df_sub['lot'],
        lat = df_sub['lat'],
        text = df_sub['text'],
        marker = dict(
            size = df_sub['Freq'],
            color = colors[i],
            line_color='rgb(40,40,40)',
            line_width=0.5
        ),
            name = '{0} - {1}'.format(lim[0],lim[1])))

fig.update_layout(
        title_text = 'Reviews negativas realizadas por usuarios ordenados por Ciudad y marcas<br>',
        showlegend = True,
        geo = dict(
            scope = 'usa',
            landcolor = 'rgb(217, 217, 217)',
        )
    )

fig.show()

	id	brand	categories	dateAdded	dateUpdated	ean	keys	manufacturer	manufacturerNumber	name	...	reviews.id	reviews.numHelpful	reviews.rating	reviews.sourceURLs	reviews.text	reviews.title	reviews.userCity	reviews.userProvince	reviews.username	upc
0	AV13O1A8GV-KLJ3akUyj	Universal Music	Movies, Music & Books,Music,R&b,Movies & TV,Mo...	2017-07-25T00:52:42Z	2018-02-05T08:36:58Z	6.02537E+11	602537205981,universalmusic/14331328,universal...	Universal Music Group / Cash Money	14331328	Pink Friday: Roman Reloaded Re-Up (w/dvd)	...	NaN	0.0	5	https://redsky.target.com/groot-domain-api/v1/...	i love this album. it's very good. more to the...	Just Awesome	Los Angeles	NaN	Joshua	6.02537E+11
1	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	Good flavor. This review was collected as part...	Good	NaN	NaN	Dorothy W	73416000391
2	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	Good flavor.	Good	NaN	NaN	Dorothy W	73416000391
3	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	113026909.0	NaN	1	https://www.walmart.com/reviews/product/43383370	I read through the reviews on here before look...	Disappointed	NaN	NaN	Rebecca	67981934427
4	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	171267657.0	NaN	1	https://www.walmart.com/reviews/product/43383370	My husband bought this gel for us. The gel cau...	Irritation	NaN	NaN	Walker557	67981934427

	id	brand	categories	dateAdded	dateUpdated	ean	keys	manufacturer	manufacturerNumber	name	...	reviews.id	reviews.numHelpful	reviews.rating	reviews.sourceURLs	reviews.text	reviews.title	reviews.userCity	reviews.userProvince	reviews.username	upc
0	AV13O1A8GV-KLJ3akUyj	Universal Music	Movies, Music & Books,Music,R&b,Movies & TV,Mo...	2017-07-25T00:52:42Z	2018-02-05T08:36:58Z	6.02537E+11	602537205981,universalmusic/14331328,universal...	Universal Music Group / Cash Money	14331328	Pink Friday: Roman Reloaded Re-Up (w/dvd)	...	NaN	0.0	5	https://redsky.target.com/groot-domain-api/v1/...	i love this album. it's very good. more to the...	Just Awesome	Los Angeles	NaN	Joshua	6.02537E+11
1	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor. this review was collected as part...	Good	NaN	NaN	Dorothy W	73416000391
2	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor.	Good	NaN	NaN	Dorothy W	73416000391
3	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	113026909.0	NaN	1	https://www.walmart.com/reviews/product/43383370	i read through the reviews on here before look...	Disappointed	NaN	NaN	Rebecca	67981934427
4	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	171267657.0	NaN	1	https://www.walmart.com/reviews/product/43383370	my husband bought this gel for us. the gel cau...	Irritation	NaN	NaN	Walker557	67981934427

	id	brand	categories	dateAdded	dateUpdated	ean	keys	manufacturer	manufacturerNumber	name	...	reviews.id	reviews.numHelpful	reviews.rating	reviews.sourceURLs	reviews.text	reviews.title	reviews.userCity	reviews.userProvince	reviews.username	upc
0	AV13O1A8GV-KLJ3akUyj	Universal Music	Movies, Music & Books,Music,R&b,Movies & TV,Mo...	2017-07-25T00:52:42Z	2018-02-05T08:36:58Z	6.02537E+11	602537205981,universalmusic/14331328,universal...	Universal Music Group / Cash Money	14331328	Pink Friday: Roman Reloaded Re-Up (w/dvd)	...	NaN	0.0	5	https://redsky.target.com/groot-domain-api/v1/...	i love this album its very good more to the hi...	Just Awesome	Los Angeles	NaN	Joshua	6.02537E+11
1	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor this review was collected as part ...	Good	NaN	NaN	Dorothy W	73416000391
2	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor	Good	NaN	NaN	Dorothy W	73416000391
3	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	113026909.0	NaN	1	https://www.walmart.com/reviews/product/43383370	i read through the reviews on here before look...	Disappointed	NaN	NaN	Rebecca	67981934427
4	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	171267657.0	NaN	1	https://www.walmart.com/reviews/product/43383370	my husband bought this gel for us the gel caus...	Irritation	NaN	NaN	Walker557	67981934427

	id	brand	categories	dateAdded	dateUpdated	ean	keys	manufacturer	manufacturerNumber	name	...	reviews.id	reviews.numHelpful	reviews.rating	reviews.sourceURLs	reviews.text	reviews.title	reviews.userCity	reviews.userProvince	reviews.username	upc
0	AV13O1A8GV-KLJ3akUyj	Universal Music	Movies, Music & Books,Music,R&b,Movies & TV,Mo...	2017-07-25T00:52:42Z	2018-02-05T08:36:58Z	6.02537E+11	602537205981,universalmusic/14331328,universal...	Universal Music Group / Cash Money	14331328	Pink Friday: Roman Reloaded Re-Up (w/dvd)	...	NaN	0.0	5	https://redsky.target.com/groot-domain-api/v1/...	i love this album its very good more to the hi...	Just Awesome	Los Angeles	NaN	Joshua	6.02537E+11
1	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor this review was collected as part ...	Good	NaN	NaN	Dorothy W	73416000391
2	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor	Good	NaN	NaN	Dorothy W	73416000391
3	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	113026909.0	NaN	1	https://www.walmart.com/reviews/product/43383370	i read through the reviews on here before look...	Disappointed	NaN	NaN	Rebecca	67981934427
4	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	171267657.0	NaN	1	https://www.walmart.com/reviews/product/43383370	my husband bought this gel for us the gel caus...	Irritation	NaN	NaN	Walker557	67981934427

	id	brand	categories	dateAdded	dateUpdated	ean	keys	manufacturer	manufacturerNumber	name	...	reviews.id	reviews.numHelpful	reviews.rating	reviews.sourceURLs	reviews.text	reviews.title	reviews.userCity	reviews.userProvince	reviews.username	upc
0	AV13O1A8GV-KLJ3akUyj	Universal Music	Movies, Music & Books,Music,R&b,Movies & TV,Mo...	2017-07-25T00:52:42Z	2018-02-05T08:36:58Z	6.02537E+11	602537205981,universalmusic/14331328,universal...	Universal Music Group / Cash Money	14331328	Pink Friday: Roman Reloaded Re-Up (w/dvd)	...	NaN	0.0	5	https://redsky.target.com/groot-domain-api/v1/...	i love this album its very good more to the hi...	Just Awesome	Los Angeles	NaN	Joshua	6.02537E+11
1	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor this review was collected as part ...	Good	NaN	NaN	Dorothy W	73416000391
2	AV14LG0R-jtxr-f38QfS	Lundberg	Food,Packaged Foods,Snacks,Crackers,Snacks, Co...	2017-07-25T05:16:03Z	2018-02-05T11:27:45Z	73416000391	lundbergorganiccinnamontoastricecakes/b000fvzw...	Lundberg	574764	Lundberg Organic Cinnamon Toast Rice Cakes	...	100209113.0	NaN	5	https://www.walmart.com/reviews/product/29775278	good flavor	Good	NaN	NaN	Dorothy W	73416000391
3	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	113026909.0	NaN	1	https://www.walmart.com/reviews/product/43383370	i read through the reviews on here before look...	Disappointed	NaN	NaN	Rebecca	67981934427
4	AV16khLE-jtxr-f38VFn	K-Y	Personal Care,Medicine Cabinet,Lubricant/Sperm...	2017-07-25T16:26:19Z	2018-02-05T11:25:51Z	67981934427	kylovesensualitypleasuregel/b00u2whx8s,0679819...	K-Y	67981934427	K-Y Love Sensuality Pleasure Gel	...	171267657.0	NaN	1	https://www.walmart.com/reviews/product/43383370	my husband bought this gel for us the gel caus...	Irritation	NaN	NaN	Walker557	67981934427

Laboratorio 9.¶

Visualizaciones interactivas¶

Carga de librerias¶

Visualizacion de datos¶

Limpieza y Procesamiento de Datos¶

Eliminacion de NAN's¶

De Mayuscula a minuscula¶

Eliminación de caracteres especiales¶

Eliminacion de URLs¶

Quitar emojis¶

Eliminacion de Stopwords¶

Histograma de cantidad de reviews por rating¶

Positivas¶

Negativas¶

Teniendo en cuenta la cantidad de palabras positivas y negativas del review determine quétan positivo, negativo o neutral es el mismo para el producto.¶

Mapa #1¶

Mapa 2¶

Mapa 3¶

Mapa 4¶